Prof. Dr. Jacob Ziv
| 27.11.1931 | Geboren in Tiberias, Israel. |
| 1950-57 | Studium der Elektrotechnik am TECHNION-Israel Institute of Technology, Haifa;B.Sc 1954; Dipl.-Ing. 1955; M.Sc. 1957. |
| 1959-62 | Studium der Elektrotechnik am Massachusetts Institute of Technology, U.S.A.; D.Sc. 1962. |
| 1962-68 | Leiter der Abteilung für die Kommunikation in der Wissenschatt de5 israelischen Verteidigungsministeriums. |
| 1968-70 | Mitarbeiter im techn. Stab der Bell Laboratorien in Murray Hill, U.S.A. |
| 1970- | Lehrtätigkeit an der elektrotechn. Fakultät des TECHNION; dort "Herman Gross Professor of Electrical Engineering" und gleichzeitig "Technion Distinguished Professor". |
| 1974-76 | Dekan der elektrotechnischen Fakultät und |
| 1978-82 | Vizepräsident für akademische Angelegenheiten am TECHNION. |
| 1982 | Gewähltes Mitglied der Israelischen Akademie der Wissenschaften. |
| 1988 | Gewähltes auswärtiges Mitglied der U.S.-amerikanischen Nationalakademie für Ingenieurwesen |
| 1985-91 | Vorsitzender im Israelischen Komitee für Planung und Bezuschussung der Universitäten. |
| 1996- | Präsident der Israelischen Nationalakademie für Natur- und Geisteswissenschaften. |
| 1976,1979 | Auszeichnung der "IEEE Information Theory Society" für die beste Publikation. |
| 1993 | Israel-Preis für exakte Wissenschaften. |
| 1995 | a) Richard W. Hamming-Medaille des IEEE.
b) Internationaler Marconi-Preis. |
| 1997 | a) Shannon-Preis der "IEEE Information Theory Society".
b) Paris-Kanellakis-Preis für Theorie und Praxis des ACM. |
Assume that you enter a text into your PC in order to process it, save
it, or send it over the Internet afterwards. This text is initially converted
to a string of ones and zeros, which are known as bits. Saving and sending
the text gets faster and cheaper as the coding procedure works with fewer
and fewer bits. Samuel Morse, one of the early pioneers of communication
technology, recognized this when he assigned especially short Morse signals
to frequently occurring letters of the alphabet. Cutting down
on the amount of data that has to be transmitted is called data compression.
Even greater efficiency can be achieved if one takes frequently occurring
longer character strings into account. In normal English texts the character
string the is much more frequent than, say, the string das,
which means that one can assign bits more sparingly. In his seminal work
on information theory in 1948 Claude E. Shannon ( 1991 Eduard Rhein Prize
showed that a minimum number of bits per character exists for
such data compression if the compression is to be lossless. However,
using the method sketched above requires going to inordinate lengths to
approximate this "entropy," i.e. the minimum number of bits per character.
Furthermore, such coding very much depends on the type of text and especially
on the language, as the examples the and das show.
A coding procedure offered by Jacob Ziv (who developed the concept and
provided the theoretical basis) and Abraham Lempel (who developed the programming
algorithm) solves this problem in a very elegant way. Any additional text
is encoded by searching for already encoded segments - the longer they
are, the better- in dynamically linked memory and by using these as prefixes
for new code words, for example them. Such a coding procedure is universal,
that is, independent of the type and
language of the text. As Ziv was able to show in the 1970s, for uniform
texts it astonishingly quickly approximates the ideal goal, namely "entropy"
as the minimum number of bits in lossless data compression. Thereafter,
the original text can be recovered using an equally simple procedure.
Experts consider this coding procedure the most important step to date
in the development of text coding.